Then, a validation database was used to confirm the previously determined results using a new set of data. We also created a map to show which software will give the lowest error for the different flow and well parameters. Also, for different conditions, we calculated the different statistical parameters for the calculated pressure from each correlation including normalized root mean square error (NRMSE), coefficient of determination (R 2), and the standard deviation (STD). We could determine the expected average percent error (APE) and average absolute percent error (AAPE) for each correlation for different flow conditions. The target was to determine the best correlation(s) for each case and establish guidelines to help petroleum engineers in selecting the best correlation when actual bottom-hole flowing pressure data is unavailable. 14 correlations were used from Software “A” and 26 correlations were used from Software “B” to calculate the pressure drop in the tubing for each case. A database of 537 bottom hole flowing pressure data points was used which covered 33 different flowing, well geometry, and tubing diameter conditions. We studied and evaluated the different multiphase flow correlations using two commercial software (A and B). The modeling of single-phase flow is considered the simplest case, but considering multiphase flow (oil, gas, and water) makes it more challenging. Petroleum engineers model existing conditions of the fluid flow to help them in predicting wells’ future performance. Accurate production forecast of gas wells helps in decision making and maximizing reserves. Gas production represents an important source of energy used in different industries.

Fluid flow correlations